博碩士論文 100521088 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:11 、訪客IP:3.235.41.241
姓名 柯廷翰(Ting-Han Ke)  查詢紙本館藏   畢業系所 電機工程學系
論文名稱 考慮配電系統三相故障之具低電壓穿越能力之智慧型太陽光電系統
(Intelligent PV System with LVRT under Grid Faults for Distribution System)
相關論文
★ 機場地面燈光更新工程 -以桃園國際機場南邊跑滑道為例★ 多功能太陽能微型逆變器之研製
★ 應用於儲能系統之智慧型太陽光電功率平滑化控制★ 利用智慧型控制之三相主動式電力濾波器的研製
★ 應用於內藏式永磁同步馬達之智慧型速度控制及最佳伺服控制頻寬研製★ 新型每安培最大轉矩控制同步磁阻馬達驅動系統之開發
★ 同步磁阻馬達驅動系統之智慧型每安培最大轉矩追蹤控制★ 利用適應性互補式滑動模態控制於同步磁阻馬達之寬速度控制
★ 具智慧型太陽光電功率平滑化控制之微電網電能管理系統★ 高性能同步磁阻馬達驅動系統之 寬速度範圍控制器發展
★ 智慧型互補式滑動模態控制系統實現於X-Y-θ三軸線性超音波馬達運動平台★ 智慧型同動控制之龍門式定位平台及應用
★ 利用智慧型滑動模式控制之五軸主動式磁浮軸承控制系統★ 智慧型控制雙饋式感應風力發電系統之研製
★ 無感測器直流變頻壓縮機驅動系統之研製★ 應用於模組化輕型電動車之類神經網路控制六相永磁同步馬達驅動系統
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   [檢視]  [下載]
  1. 本電子論文使用權限為同意立即開放。
  2. 已達開放權限電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。
  3. 請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。

摘要(中) 本論文提出兩種併網型太陽光電系統於故障期間之實虛功智慧型控制法,此二智慧型控制法皆同時符合再生能源併網低電壓穿越規範與變流器之最大電流限制。所提之二智慧型控制器分別為機率小波模糊類神經網路控制器,以及非對稱歸屬函數之TSK型機率模糊類神經網路控制器。論文中將詳細介紹兩種智慧型控制器的架構與線上學習法則,並證明其收斂性分析。當併網型太陽光電系統發生電壓故障時,控制器會依據低壓穿越規範所規範的虛功補償參考值,調整注入市電系統之虛功量,並能使太陽光電系統所產生的實功與注入市電的實功維持平衡。此外,本研究還提出兩種雙模式控制策略可於故障期間消除直流鏈電壓的波動。還有,在故障期間,注入市電系統電流大小加入了最大電流限制以降低過電流發生的風險。最後展示一些實驗結果以驗證所提方法之成效。
摘要(英) Two active and reactive power control schemes using intelligent control for grid-connected three-phase photovoltaic (PV) system during grid faults are proposed in this study. The control schemes are based on a ratio between active and reactive power which meet the low voltage ride through (LVRT) regulations and inverter maximum current limit simultaneously. Moreover, two intelligent controls based on probabilistic wavelet fuzzy neural network (PWFNN) and Takagi-Sugeno-Kang type probabilistic fuzzy neural network with asymmetric membership function (TSKPFNN-AMF) are developed to control the reactive power injected into the grid and balance the active power between the power generated by the PV and the power delivered into the grid under grid faults. The intelligent controllers regulate the value of reactive power to a new reference value which complies with the requirements of LVRT under grid faults. Furthermore, two dual-mode operation control strategies, which can eliminate the fluctuation of DC-link bus voltage under grid faults, are also discussed. In addition, to reduce the risk of over-current during the LVRT operation, a current limit is predefined in current injection. Finally, some experimental results are presented in order to validate the effectiveness of the proposed control.
關鍵字(中) ★ 配電系統三相故障
★ 低電壓穿越
★ 太陽光電系統
★ 虛功控制
★ 機 率小波模糊類神經網路
★ 非歸屬函數之TSK型機率模糊類神經網路
關鍵字(英) ★ Photovoltaic system
★ PWFNN
★ TSKPFNN-AMF
★ low voltage ride through
★ grid faults
★ reactive power control
論文目次 中文摘要 i
英文摘要 ii
誌謝 iii
目錄 iv
圖目錄 vii
表目錄 xi
第 1 章 緒論 1
1.1 研究背景 1
1.2 文獻回顧 3
1.3 論文大綱 6
1.4 本文貢獻 6
第 2 章 太陽光電系統簡介 7
2.1 簡介 7
2.2 太陽能電池特性簡介 7
2.3 太陽能電池最大功率點追蹤 11
2.4 三相座標軸轉換之分析 12
2.4.1 靜止座標軸 14
2.4.2 同步旋轉座標軸 15
2.4.3 三相功率計算 16
2.5 市電角度偵測策略 17
2.5.1 三相線電壓軸轉換法 17
2.5.2 三相電壓濾波法 18
2.5.3 三相鎖相迴路法 19
2.6 變流器之實虛功控制與電流控制 20
2.7 硬體設備 22
2.7.1 可程控直流電源供應器(具太陽能電池陣列模擬功能) 23
2.7.2 升壓轉換器、變流器 25
2.7.3 三相變壓器 27
2.7.4 交流電源供應器 28
2.7.5 資料擷取卡 30
第 3 章 配電系統三相故障分析 32
3.1 簡介 32
3.2 故障型態分析 32
3.3 正負序分析 37
3.4 正負序偵測 40
3.5 故障電壓偵測與低電壓穿越規範 48
第 4 章 機率小波模糊類神經網路之太陽光電系統 51
4.1 系統簡介 51
4.2 升壓轉換器雙模式控制策略 52
4.3 機率小波模糊類神經網路架構 55
4.4 機率小波模糊類神經網路線上學習法則 58
4.5 機率小波模糊類神經網路之收斂性分析 60
4.6 實作與討論 62
4.6.1 配電系統單相對地故障(Mode I) 62
4.6.2 配電系統單相對地故障(Mode II) 65
4.6.3 配電系統兩相之間故障(Mode II) 68
第 5 章 非對稱歸屬函數之TSK型機率模糊類神經網路之太陽光電系統 71
5.1 簡介 71
5.2 雙模式控制策略 72
5.3 非對稱歸屬函數之TSK型機率模糊類神經網路架構 74
5.4 非對稱歸屬函數之TSK型機率模糊類神經網路線上學習法則 77
5.5 非對稱歸屬函數之TSK型機率模糊類神經網路之收斂性分析 80
5.6 實作與討論 82
5.6.1 配電系統兩相對地故障(Mode I) 83
5.6.2 配電系統兩相對地故障(Mode II) 86
5.6.3 配電系統兩相對地故障(Mode II) 89
第 6 章 結論與未來研究方向 92
6.1 結論 92
6.2 未來研究方向 92
參考文獻 93
作者簡歷 98
參考文獻 [1] Global Market Outlook for Photovoltaics 2013-2017, 2013, [Online]. Available: http://www.epia.org/home/
[2] 經濟部能源局,2012年能源產業技術白皮書,經濟部能源局,台北市,2012。
[3] F. Blaabjerg, R. Teodorescu, M. Liserre, and A. V. Timbus, “Overview of control and grid synchronization for distributed power generation systems,” IEEE Trans. Indust. Electron., vol. 53, no. 5, pp. 1398-1409, Oct. 2006.
[4] M. H. J. Bollen, “Characterisation of voltage sags experienced by three-phase adjustable-speed drives,” IEEE Trans. Power Del., vol. 12, no. 4, pp. 1666-1671, Oct. 1997.
[5] V. Ignatova, P. Granjon, and S. Bacha, “Space vector method for voltage dips and swells analysis,” IEEE Trans. Power Del., vol. 24, no. 4, pp. 2054-2061, Oct. 2009.
[6] Grid Code High and Extra High Voltage, E.ON Netz GmbH, Bayreuth, Germany, Apr. 2006. [Online]. Available: http://www.nationalgrid.com/uk
[7] P. Rodriguez, A. V. Timbus, R. Teodorescu, M. Liserre, and F. Blaabjerg, “Flexible active power control of distributed power generation systems during grid faults,” IEEE Trans. Indus. Electron., vol. 54, no. 5, pp. 2583-2592, Oct. 2007.
[8] P. Rodríguez, A. Timbus, R. Teodorescu, M. Liserre, and F. Blaabjerg, “Reactive power control for improving wind turbine system behavior under grid faults,” IEEE Trans. Power Electron., vol. 24, no. 7, pp. 1798-1801, Jul. 2009.
[9] M. Castilla, J. Miret, J. L. Sosa, J. Matas, and L. García de Vicuña, “Grid-fault control scheme for three-phase photovoltaic inverters with adjustable power quality characteristics,” IEEE Trans. Power Electron., vol. 25, no. 12, pp. 2930-2940, Dec. 2010.
[10] M. Reyes, P. Rodriguez, S. Vazquez, A. Luna, R. Teodorescu, and J. M. Carrasco, “Enhanced decoupled double synchronous reference frame current controller for unbalanced grid-voltage conditions,” IEEE Trans. Power Electron., vol. 27, no. 9, pp. 3934-3943, Sep. 2012.
[11] C. T. Lee, C. W. Hsu, and P. T. Cheng, “A low-voltage ride-through technique for grid-connected converters of distributed energy resources,” IEEE Trans. Indus. Appl., vol. 47, no. 4, pp. 1821-1832, Jul./Aug. 2011.
[12] J. Miret, M. Castilla, A. Camacho, L. García de Vicuña, and J. Matas, “Control scheme for photovoltaic three-phase inverters to minimize peak currents during unbalanced grid-voltage sags,” IEEE Trans. Power Electron., vol. 27, no. 10, pp. 4262-4271, Oct. 2012.
[13] A. Camacho, M. Castilla, J. Miret, J. C. Vasquez, and E. Alarcón-Gallo, “Flexible voltage support control for three-phase distributed generation inverters under grid fault,” IEEE Trans. Power Electron., vol. 60, no. 4, pp. 1429-1441, Apr. 2013.
[14] J. Miret, A. Camacho, M. Castilla, L. García de Vicuña, and J. Matas, “Control scheme with voltage support capability for distributed generation inverters under voltage sags,” IEEE Trans. Power Electron., vol. 28, no. 11, pp. 5252-5262, Nov. 2013.
[15] D. Xie, Z. Xu, L. Yang, J. Østergaard, Y. Xue, and K. P. Wong, “A comprehensive LVRT control strategy for DFIG wind turbines with enhanced reactive power support,” IEEE Trans. Power Sys., to be published, 2013.
[16] F. J. Lin, L. T. Teng, P. H. Shieh, and Y. F. Li, “Intelligent controlled-wind-turbine emulator and induction-generator system using RBFN,” IET Electr. Power Appl., vol. 153, no. 4, pp. 608-618, Jul. 2006.
[17] F. J. Lin, M. S. Huang, P. Y. Yeh, H. C. Tsai, and C. H. Kuan, “DSP-based probabilistic fuzzy neural network control for Li-ion battery charger,” IEEE Trans. Power Electron., vol. 27, no. 8, pp. 3782-3794, Aug. 2012.
[18] W. M. Lin and C. M. Hong, “A new Elman neural network-based control algorithm for adjustable-pitch variable-speed wind-energy conversion systems,” IEEE Trans. Power Electron., vol. 26, no. 2, pp. 473-481, Feb. 2011.
[19] I. B. Kucukdemiral and G. Cansever, “Formalization of a noval Sugeno type adaptive fuzzy sliding mode controller for a class of nonlinear systems,” in Proc. IEEE International Conference Mechatronics, pp. 717-720, 2005
[20] Z. L. Gaing, “Wavelet-based neural network for power disturbance recognition and classification,” IEEE Trans. Power Del., vol. 19, no. 4, pp. 1560-1568, Oct. 2004.
[21] N. M. Pindoriya, S. N. Singh, and S. K. Singh, “An adaptive wavelet neural network-based energy price forecasting in electricity markets,” IEEE Trans. Power Sys., vol. 23, no. 3, pp. 1423-1432, Aug. 2008.
[22] C. H. Lu, “Wavelet fuzzy neural networks for identification and predictive control of dynamic systems,” IEEE Trans. Indus. Electron., vol. 58, no. 7, pp. 3046-3058, Jul. 2011.
[23] M. Davanipoor, M. Zekri, and F. Sheikholeslam, “Fuzzy wavelet neural network with an accelerated hybrid learning algorithm," IEEE Trans. Fuzzy Sys., vol. 20, no. 3, pp. 463-470, Jun. 2012.
[24] Z. Liu and H. X. Li, “A probabilistic fuzzy logic system for modeling and control,” IEEE Trans. Fuzzy Sys., vol. 13, no. 6, pp. 848-859, Dec. 2005.
[25] H. X. Li and Z. Liu, “A probabilistic neural-fuzzy learning system for stochastic modeling,” IEEE Trans. Fuzzy Sys., vol. 16, no. 4, pp. 898-908, Aug. 2008.
[26] N. Sozhamadevi, R. S. L. Delcause, and Dr. S. Sathiyamoorthy, “Design and implementation of probabilistic fuzzy logic control system,” in Proc. IEEE Conf. Emerging Trends in Science, Engineering and Technology, pp. 523-531, 2012.
[27] H. Y. Pan, C. H. Lee, F. K. Chang, and S. K. Chang, “Construction of asymmetric type 2 fuzzy membership function and application in time series prediction,” in Proc. Int. Conf. Machine Learning and Cybernetics, pp. 2024-2030, 2007.
[28] K. H. Cheng, C. F. Hsu, C. M. Lin, T. T. Lee, and C. Li, “Fuzzy neural sliding mode control for dc-dc converters using asymmetric gaussian membership functions,” IEEE Trans. Indust. Electron., vol. 54, no. 3, pp. 1528-1536, 2007
[29] C. H. Lee, T. W. Hu, C. T. Lee, and Y. C. Lee, “A recurrent interval type-2 fuzzy neural network with asymmetric membership functions for nonlinear system identification,” in Proc. IEEE Conf. Fuzzy System, pp. 1496-1502, 2008.
[30] K. Ishaque, Z Salam, M Amjad, and S Mekhulef, “An Improved Particle Swarm Optimization (PSO)–Based MPPT for PV With Reduced Steady-State Oscillation,” IEEE Trans. Power Electron., vol. 27, no. 8, pp. 3627-3638, Aug. 2012.
[31] Y. H. Yang and F. Blaabjerg, “A modified P&O MPPT algorithm for single phase PV systems based on deadbeat control,” in Proc. 6th IET Inter. Conf. Power Electronics, Machines and Drives, Mar. 2012.
[32] 黃仲欽,交流電動機控制,交流電動機課程講義,民國97年。
[33] N. Mohan, T. M. Undeland, W. P. Robbins, Power electronics, 1989.
[34] 使用手冊,可程控直流電源供應器(具太陽能電池陣列模擬) 62000H系列使用手冊,Chroma,2012。
[35] 使用手冊,太陽能電池陣列模擬虛擬儀控面板 62000H系列使用手冊,Chroma,2012年三月。
[36] 呂宗翰,智慧型控制雙饋式感應風力發電系統之研製,國立中央大學,碩士論文,2010年六月。
[37] H. Saadat, Power System Analysis, McGraw-Hill, 2004.
[38] User Manual, User’s Manual PCR-LE series, KIKUSUI, Feb. 2013.
[39] G. Saccomando, J. Svensson, and A. Sannino, “Improving voltage disturbance rejection for variable-speed wind turbines,” IEEE Trans. Energy Convers., vol. 17, no. 3, pp. 422-428, Sep. 2002.
[40] R. Teodorescu, M. Liserre, and P. Rodriguez, Grid converters for photovoltaic and wind power systems. John Wiley & Sons. Ltd. 2011.
指導教授 林法正(Faa-Jeng Lin) 審核日期 2013-8-9
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明